Analytics Engineer

As an Analytics Engineer, you will design and maintain data governance frameworks, build internal data tools and dashboards, architect web-scraping systems for competitive intelligence, and apply machine learning models to derive business insights.

Overview

Department

Product

Job type

Full time

Compensation

Salary not specified

Location

Singapore, Southeast Asia

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Responsibilities

User Behavior Data Governance: Design, implement, develop and maintain scalable governance frameworks to ensure the accuracy, consistency, and integrity of user-event data. Collaborate cross-functionally to define tracking strategies, conduct audits, and enforce best practices

Internal Data Tool Development: Build, test, and deploy internal data tools and dashboards using JavaScript or Python. Develop automated data pipelines, user-friendly analytics interfaces, and self-service solutions that empower business teams

Competitive Intelligence & Data Scraping: Architect and maintain automated web-scraping systems to gather competitor insights—such as pricing, feature sets, and market trends. Ensure solutions are efficient, robust, and compliant with legal and ethical guidelines.

Machine Learning & Advanced Analytics: Apply statistical methods or machine learning models to unlock business value—such as forecasting user behavior, predicting churn, or optimizing product features.

Requirements

Expert-level SQL and strong Python or JavaScript abilities for data transformation and tool development

Proven experience implementing data governance or event instrumentation processes (e.g., Segment, GA4, Mixpanel)

Data Pipeline & ETL/ELT Expertise: Track record designing and maintaining data pipelines using frameworks like dbt, Airflow, Talend, or similar

Web Scraping Competency: Comfortable with scraping technologies and libraries, and adept at orchestrating automated scraping workflows.

Analytical & Problem-Solving Skills: Demonstrated ability to break down complex problems, translate stakeholder needs, and produce clean, documented data solutions

Collaboration & Communication: Excellent at bridging terminology between technical and business stakeholders. Clear, concise in written and verbal communication

Nice-to-Have Qualifications

Experience with cloud data warehouses (Snowflake, BigQuery, Redshift) and BI tools (Looker, Tableau)

Familiarity with software development workflows: Git, code reviews, modular design, CI/CD

Hands-on knowledge of machine learning libraries (scikit-learn, TensorFlow/PyTorch).

Front-end development experience (React, Vue, Node.js) to build polished internal tools.

Awareness of data privacy, legal compliance, and ethical considerations in scraping and data governance.